The willingness to adopt the Internet of Things (IoT) conception in Taiwan’s construction industry
Internet of Things (IoT) conception has become a popular trend among industries. Many have already adopted the technology and put it into practice. IoT can incentive and change the way people conduct business in the construction industry. The objective of the research is to figure out the impact factors that influence practitioners’ willingness to adopt IoT in Taiwan’s construction industry. The hypothesis was developed based on a comprehensive literature review and the concept of the Unified Theory of Acceptance and Use of Technology (UTUAT). The UTUAT framework and hypotheses developed included 5 main hypotheses, 6 aspects and 33 stems. A pilot study aimed at experienced practitioners in the industry was carried out before the full-scale survey to adjust the stems. The adjusted questionnaire including 31 stems belonging to 7 aspects was then distributed to practitioners. A total of 282 valid questionnaires distributed were collected and 6 types of analysis (descriptive statistics, reliability, validity, t-test, one-way of variance, and structural equation modelling). The findings including (1) anticipated benefits significantly affect the users’ willingness to adopt IoT; (2) anticipated efforts significantly affect the users’ willingness to adopt IoT; (3) societal expectations significantly affect the users’ willingness to adopt IoT.
Keyword : Internet of Things (IoT), Unified Theory of Acceptance and Use of Technology (UTAUT) model, Technology Acceptance Model (TAM), extension of the Technology Acceptance Model, construction industry, structural equation model
This work is licensed under a Creative Commons Attribution 4.0 International License.
Agarwal, R., & Prasad, J. (1997). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9, 204–224. https://doi.org/10.1287/isre.9.2.204
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl, & J. Beckman (Eds.), Action control: from cognition to behaviour (pp. 11–39). Springer. https://doi.org/10.1007/978-3-642-69746-3_2
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978 (91)90020-T
Ajzen, I., & Fishbein, M. (1975). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918. https://doi.org/10.1037/0033-2909.84.5.888
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior (Paperback ed.). Prentice-Hall.
Al-Khaldi, M. A., & Wallace, R. S. O. (1999). The influence of attitudes on personal computer utilization among knowledge workers: the case of Saudi Arabia. Information & Management, 36(4), 185–204. https://doi.org/10.1016/S0378-7206(99)00017-8
Armitage, C. J., & Conner, M. (2001). Efficacy of the Theory of Planned Behaviour: A meta-analytic review. British Journal of Social Psychology, 40(4), 471–499. https://doi.org/10.1348/014466601164939
Alaa, M., Zaidan, A. A., Zaidan, B. B., Talal, M., & Kiah, M. L. M. (2017). A review of smart home applications based on Internet of Thing. Journal of Network and Computer Applications, 97, 48–65. https://doi.org/10.1016/j.jnca.2017.08.017
Bagozzi, R. P., & Yi, T. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327
Bhargav, D., Silvain, K., Ergo, P., Jan, H., Vishal, S., Kary, F., & Lauri, K. (2015). Intelligent products: Shifting the production control logic in construction (with Lean and BIM). In Proceedings of the 23rd Annual Conference of the International Group for Lean Construction (pp. 341–350). Perth, Australia.
Bozionelos, N. (1996). Psychology of computer use: XXXIX. Prevalence of computer anxiety in British managers and professionals. Psychological Reports, 78(3), 995–1002. https://doi.org/10.2466/pr0.19188.8.131.525
Chen, G., Wang, E., Sun, X., & Lu, Y. (2016). An intelligent approval system for city construction based on cloud computing and big data. International Journal of Grid and High Performance Computing, 8(3), 57–69. https://doi.org/10.4018/IJGHPC.2016070104
Chi, B., Meng, H., Zhai, K., Zhai, G., & Liu, Y. (2017). Big data in urban construction archives and urban management: Detected underground pipes alignment with urban construction records. In IEEE International Conference on Big Knowledge (pp. 173–178). https://doi.org/10.1109/ICBK.2017.53
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339. https://doi.org/10.2307/249008
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50. https://doi.org/10.1177/002224378101800104
Gates, B. (1995). The road ahead. Viking Penguin.
Glaeser, E. L., Kominers, D., Luca, M., & Naik, N. (2018). Big data and big cities: The promises and limitations of improved measures of urban life. Economic Inquiry, 56(1), 114–137. https://doi.org/10.1111/ecin.12364
Gubbia, J., Buyya, R., Marusica, S., & Palaniswami, M.(2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010
Hair, J., Anderson, R., Tatham, R., & Black, W. (1998). Multivariate data analysis (5th ed.). Prentice Hall Publishing.
Jöreskog, K. G. (1993). Testing structural equation models. In K. A. Bollen, & J. S. Long (Eds.), Testing structural equation models (pp. 294–316). Sage.
Jia, M., Komeily, A., Wang, Y., & Srinivasan, R. S. (2019). Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications. Automation in Construction, 101, 111–126. https://doi.org/10.1016/j.autcon.2019.01.023
Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. Management Information Systems, 23(2), 183–213. https://doi.org/10.2307/249751
Lee, I., & Lee, K. (2015). The Internet of Things (IOT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431–440. https://doi.org/10.1016/j.bushor.2015.03.008
Leo, M., Battisti, F., Carli, M., & Neri, A. (2014). A federated architecture approach for Internet of Things security. In Proceedings of 2014 Euro Med Telco Conference (EMTC). Naples, Italy. https://doi.org/10.1109/EMTC.2014.6996632
Lin, J., Yu, W., Zhang, N., Yang, X., Zhang, H., & Zhao, W. (2017). A survey on Internet of Things: Architecture, enabling technologies, security and privacy, and applications. IEEE Internet of Things Journal, 4(5), 1125–1142. https://doi.org/10.1109/JIOT.2017.2683200
Li, M. N. (2006). Introduction to structural equation model software AMOS and application compilation. Taipei Psychology Press.
Li, C. Z.; Xue, F., Shen, G. Q., Xu, X., & Luo, L. (2016). SWOT analysis and Internet of Things-enabled platform for prefabrication housing production in Hong Kong. Automation in Construction, 57, 74–87. https://doi.org/10.1016/j.habitatint.2016.07.002
Li, C. Z., Xue, F., Li, X., Hong, J., & Shen, G. Q. (2018). An Internet of Things-enabled BIM platform for on-site assembly services in prefabricated construction. Automation in Construction, 89, 146–161. https://doi.org/10.1016/j.autcon.2018.01.001
Lu, W., Chen, X., Peng, Y., & Shen, L. (2015). Benchmarking construction waste management performance using big data resources. Conservation and Recycling, 105, 49–58. https://doi.org/10.1016/j.resconrec.2015.10.013
Lu, W., Chen, X., Ho, D. C. W., & Wang, H. (2016). Analysis of the construction waste management performance in Hong Kong: The public and private sectors compared using big data. Journal of Cleaner Production, 112(1), 521–531. https://doi.org/10.1016/j.jclepro.2015.06.106
Lynott, P. P., & McCandless, N. J. (2000). The impact of age vs. life experience on the gender role attitudes of women in different cohorts. Journal of Women & Aging, 12(1–2), 5–21. https://doi.org/10.1300/J074v12n01_02
Mahmoud, R., Yousuf, T., Aloul, F., & Zualkernan, I. (2015). Internet of things (IoT) security: Current status, challenges and prospective measures. In Proceedings of 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST) (pp. 336–341). London, UK. https://doi.org/10.1109/ICITST.2015.7412116
McKinsey Global Institute. (2015). The Internet of Things: Mapping the value beyond the hype.
Miorandi, D., Sicari, S., & Chlamtac, I. (2012). Internet of things: vision, applications and research challenges. Ad Hoc Networks, 10(7), 1497–1516. https://doi.org/10.1016/j.adhoc.2012.02.016
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 173–239. https://doi.org/10.1287/isre.2.3.192
Ray, P. P. (2016). A survey on Internet of Things architectures. Journal of King Saud University – Computer and Information Sciences, 30(3), 291–319. https://doi.org/10.1016/j.jksuci.2016.10.003
Sethi, P., & Sarangi, S. R. (2017). Internet of Things: Architectures, protocols, and applications. Journal of Electrical and Computer Engineering, Article ID 9324035. https://doi.org/10.1155/2017/9324035
Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42, 85–92. https://doi.org/10.1287/mnsc.42.1.85
Taylor, S., & Todd, P. A. (1995a). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561–570. https://doi.org/10.2307/249633
Taylor, S., & Todd, P. A. (1995b). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137–155. https://doi.org/10.1016/0167-8116(94)00019-K
Taylor, S., & Todd, P. A. (1995c). Understanding information technology usage: a test of competing models. Information Systems Research, 6(2), 144–176. https://doi.org/10.1287/isre.6.2.144
Tan, L., & Wang, N. (2010). Future internet: The Internet of Things. In Proceedings of 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE). Faridabad, India. https://doi.org/10.1109/ICACTE.2010.5579543
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 125–143. https://doi.org/10.2307/249443
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.184.108.40.20626
Venkatesh, V., Morris, M. G., Davis, G., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Viswannathen, B. M. (2015). Aligning IoT with construction industry [Post]. LinkedIn. https://www.linkedin.com/pulse/aligning-iot-construction-industry-baalaje-ms-viswanathan/
Weiser, M., Gold, R., & Brown, J. S. (1999). The origins of ubiquitous computing research at PARC in the late 1980s. IBS Systems Journal, 38(4), 693–696. https://doi.org/10.1147/sj.384.0693
Wu, M., Lu, T. J., Ling, F. Y., Sun, J., & Du, H. Y. (2010). Research on the architecture of Internet of Things. In Proceedings of 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE). Chengdu, China.
Xu, G., Li, M., Chen, C., & Wei, Y. (2018). Cloud asset-enabled integrated IoT platform for lean prefabricated construction. Automation in Construction, 93, 123–134. https://doi.org/10.1016/j.autcon.2018.05.012
Zhong, R. Y., Peng, Y., Xue, F., Fang, J., Zou, W., Luo, H., Ng, S. T., Lu, W., Shen, G. Q. P., & Huang, G. Q. (2017). Prefabricated construction enabled by the Internet-of-Things. Automation in Construction, 76, 59–70. https://doi.org/10.1016/j.autcon.2017.01.006